Chen-Yang Cheng
Papers
4
Total Citations
102
H-Index
3
About
Dr. Chen-Yang Cheng is a leading researcher at the intersection of robotics, artificial intelligence, and smart manufacturing, whose work is pivotal to advancing Industry 4.0. His primary research areas include deep learning for robotic motion planning, cyber-physical assembly systems, and intelligent automation for factory environments. Dr. Cheng’s major contributions lie in developing optimization algorithms that enable dual-arm assembly robots to perform complex tasks with unprecedented efficiency. His most cited work, “Deep learning-based optimization for motion planning of dual-arm assembly robots” (50 citations), introduces a novel framework that significantly reduces computational time for collision-free path planning. Complementing this, his study on “Cyber-physical assembly system-based optimization for robotic assembly sequence planning” (47 citations) integrates real-time data with physical processes to streamline assembly operations. Dr. Cheng has also advanced location-based services for smart factories, proposing an adaptive tracking algorithm using wireless sensor networks to enhance robot navigation accuracy. His development of a dual-projected interference matrix algorithm further addresses critical challenges in assembly automation, reducing manpower and time costs by up to 70%. Through these innovations, Dr. Cheng is shaping the future of intelligent, autonomous manufacturing systems.
Research Focus
Key Achievements
Top Papers
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